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Comparative assessment of anthropometric and bioimpedence methods for determining adiposity

BACKGROUND: Obesity is a risk factor for different chronic conditions. Over the years, obesity has become a pandemic and it is therefore important that effective diagnostic tools are developed. Obesity is a measure of adiposity and it has become increasingly evident that anthropometric measures such...

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Autores principales: Adedia, David, Boakye, Adjoa A., Mensah, Daniel, Lokpo, Sylvester Y., Afeke, Innocent, Duedu, Kwabena O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7770549/
https://www.ncbi.nlm.nih.gov/pubmed/33385081
http://dx.doi.org/10.1016/j.heliyon.2020.e05740
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author Adedia, David
Boakye, Adjoa A.
Mensah, Daniel
Lokpo, Sylvester Y.
Afeke, Innocent
Duedu, Kwabena O.
author_facet Adedia, David
Boakye, Adjoa A.
Mensah, Daniel
Lokpo, Sylvester Y.
Afeke, Innocent
Duedu, Kwabena O.
author_sort Adedia, David
collection PubMed
description BACKGROUND: Obesity is a risk factor for different chronic conditions. Over the years, obesity has become a pandemic and it is therefore important that effective diagnostic tools are developed. Obesity is a measure of adiposity and it has become increasingly evident that anthropometric measures such as body mass index (BMI) used to estimate adiposity are inadequate. This study therefore examined the ability of different anthropometric measurements to diagnose obesity within a cross-section of Ghanaian women. METHODS: We obtained anthropometric measurements and used that to generate derived measures of adiposity such as body adiposity index (BAI) and conicity index. Furthermore we also measured adiposity using a bioimpedance analyser. Associations between these measurements and percentage body fat (%BF) were drawn in order to determine the suitability of the various measures to predict obesity. The prevalence of obesity was determined using both %BF and BMI. RESULTS: BMI, Waist and hip circumference and visceral fat (VF) were positively correlated with % BF whereas skeletal muscle mass was negatively correlated. Prevalence of obesity was 16% and 31.6% using BMI and %BF respectively. Receiver operating characteristic (ROC) analysis showed that these differences in prevalence was due to BMI based misclassification of persons who have obesity as overweight. Similar, shortfalls were observed for the other anthropometric measurements using ROC. CONCLUSIONS: No single measure investigated could adequately predict obesity as an accumulation of fat using current established cut-off points within our study population. Large scale epidemiological studies are therefore needed to define appropriate population based cut-off points if anthropometric measurements are to be employed in diagnosing obesity within a particular population.
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spelling pubmed-77705492020-12-30 Comparative assessment of anthropometric and bioimpedence methods for determining adiposity Adedia, David Boakye, Adjoa A. Mensah, Daniel Lokpo, Sylvester Y. Afeke, Innocent Duedu, Kwabena O. Heliyon Research Article BACKGROUND: Obesity is a risk factor for different chronic conditions. Over the years, obesity has become a pandemic and it is therefore important that effective diagnostic tools are developed. Obesity is a measure of adiposity and it has become increasingly evident that anthropometric measures such as body mass index (BMI) used to estimate adiposity are inadequate. This study therefore examined the ability of different anthropometric measurements to diagnose obesity within a cross-section of Ghanaian women. METHODS: We obtained anthropometric measurements and used that to generate derived measures of adiposity such as body adiposity index (BAI) and conicity index. Furthermore we also measured adiposity using a bioimpedance analyser. Associations between these measurements and percentage body fat (%BF) were drawn in order to determine the suitability of the various measures to predict obesity. The prevalence of obesity was determined using both %BF and BMI. RESULTS: BMI, Waist and hip circumference and visceral fat (VF) were positively correlated with % BF whereas skeletal muscle mass was negatively correlated. Prevalence of obesity was 16% and 31.6% using BMI and %BF respectively. Receiver operating characteristic (ROC) analysis showed that these differences in prevalence was due to BMI based misclassification of persons who have obesity as overweight. Similar, shortfalls were observed for the other anthropometric measurements using ROC. CONCLUSIONS: No single measure investigated could adequately predict obesity as an accumulation of fat using current established cut-off points within our study population. Large scale epidemiological studies are therefore needed to define appropriate population based cut-off points if anthropometric measurements are to be employed in diagnosing obesity within a particular population. Elsevier 2020-12-22 /pmc/articles/PMC7770549/ /pubmed/33385081 http://dx.doi.org/10.1016/j.heliyon.2020.e05740 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Adedia, David
Boakye, Adjoa A.
Mensah, Daniel
Lokpo, Sylvester Y.
Afeke, Innocent
Duedu, Kwabena O.
Comparative assessment of anthropometric and bioimpedence methods for determining adiposity
title Comparative assessment of anthropometric and bioimpedence methods for determining adiposity
title_full Comparative assessment of anthropometric and bioimpedence methods for determining adiposity
title_fullStr Comparative assessment of anthropometric and bioimpedence methods for determining adiposity
title_full_unstemmed Comparative assessment of anthropometric and bioimpedence methods for determining adiposity
title_short Comparative assessment of anthropometric and bioimpedence methods for determining adiposity
title_sort comparative assessment of anthropometric and bioimpedence methods for determining adiposity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7770549/
https://www.ncbi.nlm.nih.gov/pubmed/33385081
http://dx.doi.org/10.1016/j.heliyon.2020.e05740
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